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- Code:
- ECOM-G314
- Field:
- Econometrics
- Target:
- Master’s students
- Organiser:
- University of Helsinki - Economics
- Instructor:
- Jani Luoto
- Period:
- Period 2
- Format:
- Lecture
- Method:
- Contact teaching
- Venue:
- Economicum
- Enrollment:
In case of conflicting information consider the Sisu/Course/Moodle pages the primary source of information.
Aalto and Hanken economics students can enroll in their home university’s SISU! Further instructions can be found on the How to enroll page, also for other students.
Before taking and completing the course make sure that the credits can be counted towards your degree at your home university by checking which courses are included in your curriculum or by contacting your home university’s student/learning services.
Content
The course builds upon a Bachelor-level introductory course in econometrics. A central goal is to deepen the knowledge on the linear regression model in various directions, including regression with instrumental variables and heteroskedastic errors. In addition, maximum likelihood estimation and the related asymptotic tests are introduced.
The course starts with a review of the linear regression model and the small-sample and asymptotic properties of the ordinary least squares estimator and statistical inference concerning its parameters. A large part of the course is devoted to the detection of and addressing violations of the basic assumptions of the linear regression model. In particular, statistical inference based on the ordinary least squares estimator under heteroskedastic or autocorrelated errors are considered. The instrumental variables and the generalised method of moments estimators, useful in the case of endogenous regressors as well as the method of maximum likelihood, widely applicable in econometrics, also introduced. Throughout the course, the emphasis is on the practical aspects of econometric modelling instead of the foundations of statistical inference. The models and methods are illustrated by means of Monte Carlo simulations and empirical applications.
Learning outcomes
After the course, the student should
- Be very familiar with the interpretation of and statistical inference in the linear regression model in the cross-sectional context
- Be familiar with the properties of the ordinary least squares, instrumental variables and the generalised method of moments estimators
- Understand the basic properties of the maximum likelihood estimator and the related asymptotic tests
- Be able to critically read empirical economic research employing methods covered in the course, to identify their potential methodological problems, to compare alternative econometric model specifications and to assess the adequacy of empirical results
- Be able to apply the models and methods covered in the course in empirical research